Deserialization of Untrusted DataWeakness · CWE-502

CVE-2025-14922

HIGH · 7.8 CVSS v3.0 Published 2025-12-23
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
81/100
Remediation priority · High
No privileges

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
Hugging Face Diffusers CogView4 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Diffusers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of checkpoints. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-27424.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

Hugging Face Diffusers CogView4 checkpoint parsing lacks proper validation of user-supplied data during deserialization. This allows attackers to craft malicious checkpoint files that execute arbitrary code when loaded by victims, exploiting the deserialization process without additional software vulnerabilities.

MitigationDo not load CogView4 checkpoints from untrusted or unverified sources. Await official patch from Hugging Face that implements safe deserialization for checkpoint loading.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Local
Complexity
Low
Privileges
None
User interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify installed diffusers version
    Run `pip show diffusers` or `python -c "import diffusers; print(diffusers.__version__)"`
    Affected if Version is unpatched and lacks safe deserialization for CogView4 checkpoints
  2. Locate CogView4 checkpoint files
    Search for model files named 'cogview4' or checkpoint files with 'cogview4' in the path: `find . -iname '*cogview4*'`
    Affected if CogView4 checkpoint files exist in the environment and could be loaded
  3. Verify checkpoint loading code
    Search codebase for `from_pretrained` or `load_checkpoint` calls referencing CogView4 models: `grep -r 'cogview4' . --include='*.py'`
    Affected if Code loads CogView4 checkpoints without additional validation
  4. Check for unsafe pickle/deserialize operations
    Inspect diffusers source for checkpoint loading logic involving pickle or unsafe deserialization: examine the checkpoint loading pipeline in diffusers library
    Affected if Checkpoint loading uses pickle or unsafe deserialization without validation
  5. Assess trust model for loaded checkpoints
    Review where and how checkpoints are loaded (local files, untrusted sources, user-uploaded): audit data flow into `from_pretrained` or similar functions
    Affected if Checkpoints are loaded from untrusted or unverified sources

Environment is affected if running an unpatched diffusers version that loads CogView4 checkpoints, particularly from untrusted or unverified sources, due to unsafe deserialization in the checkpoint parsing process.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Do not load CogView4 checkpoints from untrusted or unverified sources. Await official patch from Hugging Face that implements safe deserialization for checkpoint loading.

Have this fixed Scoped from the published advisory
  • Consultation6.0 h
  • Implementation12.0 h
  • Testing8.0 h
  • Review / QA4.0 h
30.0 hours of engineering $5,280
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-14922 in production — separate from our analysis above.

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What this is

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What belongs here
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